held in conjunction with the

23rd Intl. Conf. on Multiple Criteria Decision Making

August 2-7, 2015 in Hamburg, Germany

Scope of the Session

Research on evolutionary multiobjective optimization (EMO) started in the
mid 1980s and---unlike many multicriteria decision making (MCDM)
approaches---deals with stochastic algorithms that are able to find
multiple near Pareto-optimal solutions in a single algorithm run.
Evolutionary algorithms and other classes of metaheuristics are often used
to solve difficult problems arising in both combinatorial and continuous
multiobjective optimization. Such metaheuristics include evolutionary
algorithms, neighborhood-based search, simulated annealing, tabu search,
iterated local search, memetic algorithms, hyperheuristics, etc.

As both EMO and MCDM deal with multiobjective optimization problems, it is
natural to bring these two research fields together. The first attempts to
do so have been conducted in recent years. Joint Dagstuhl seminars as well
as several EMO tracks and workshops at the last MCDM conferences and the
MCDM sessions at the EMO conferences are most prominent examples. As this
cross-fertilization of ideas has been gathering momentum, where now really
significant research outcomes are emerging, the integration of the upcoming
EMO session into the mainstream MCDM'2015 conference is therefore a nice
opportunity to bring together researchers from the main research fields in
multiobjective optimization. It follows the tradition of EMO workshops and
special sessions during the MCDM conference, and in particular its
predecessors in 2008
in Auckland, New Zealand, in 2011
in Jyväskylä, Finland and in 2013
in Málaga, Spain.

The main focus of the EMO session is to present the most recent advances in
the EMO field to MCDM researchers in order to establish and foster collaborations
between the two fields.

Special Issue in the Computers & Operations Research Journal

Associated with the EMO session will be an upcoming Special Issue of the Computers & Operations Research journal with the focus of presenting the current state-of-the-art in EMO to the Operations Research community.
Further details can be found on the Special Issue page.